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Moderation of Adult Depression by a Polymorphism in the FKBP5 Gene and Childhood Physical Abuse in the General Population

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the FKBP5 Gene and Childhood Physical Abuse in the

General Population

Katja Appel, Christian Schwahn, Jessie Mahler, Andrea Schulz, Carsten

Spitzer, Kristin Fenske, Jan Stender, Sven Barnow, Ulrich John, Alexander

Teumer, et al.

To cite this version:

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Word count (including abstract, text, references): 6005

Moderation of Adult Depression by a Polymorphism in the

FKBP5 Gene and Childhood Physical Abuse in the General

Population

Word count (main document): 4208

Katja Appel1*, Christian Schwahn, PhD2,3,9*, Jessie Mahler1, Andrea Schulz1, Carsten Spitzer, M.D.4, Kristin Fenske5, Jan Stender5, Sven Barnow, PhD6, Ulrich John, PhD7, Alexander Teumer, Ms8, Reiner Biffar, M.D.2, Matthias Nauck, M.D.9, Henry Völzke, M.D.10, Harald Jürgen Freyberger, M.D.1 , Hans Jörgen Grabe, M.D.1

* These authors contributed equally to this work

1 Department of Psychiatry and Psychotherapy, University of Greifswald; Germany 2 Center of Oral Health, Department of Prosthetic Dentistry, Gerostomatology and Dental Materials,University of Greifswald; Germany

3 Department of Mathematics and Computer Science

4 Department of Psychosomatic Medicine and Psychotherapy, University of Hamburg; Germany

5 Department of Biological and Clinical Psychology, University of Greifswald; Germany

6 Institute of Clinical Psychology, University of Heidelberg; Germany

7 Institute of Epidemiology and Social Medicine, University of Greifswald; Germany 8 Interfacultary Institute for Genetics and Functional Genomics, University of Greifswald, Germany

9 Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Germany

10 Institute for Community Medicine, University of Greifswald; Germany

Address for correspondence:

Katja Appel

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ABSTRACT

Childhood maltreatment and depressive disorders have both been associated with a dysregulation of the hypothalamic-pituitary-adrenal (HPA) -axis. The FKBP5 gene codes for a co-chaperone regulating the glucocorticoid receptor (GR) sensitivity. Previous evidence suggests that subjects carrying the TT genotype of the FKBP5 gene single nucleotide

polymorphism (SNP) rs1360780 have an increased susceptibility to adverse effects of experimental stress. We therefore tested the hypothesis of an interaction of childhood abuse with rs1360780 in predicting adult depression. 2157 Caucasian subjects from the Study of Health in Pomerania (German general population) completed theBeck Depression Inventory (BDI-II) and Childhood Trauma Questionnaire. The DSM-IV diagnosis of major depressive disorder (MDD) was assessed by interview. Genotypes of rs1360780 were taken from the Affymetrix Human SNP Array 6.0. Significant interaction (p=0.006) of physical abuse with the TT genotype of rs1360780 was found increasing the BDI-II score to 17.4 (95% CI 12.0– 22.9) compared with 10.0 (8.2–11.7) in exposed CC/CT carriers. Likewise the adjusted odds ratio (OR) for MDD in exposed TT carriers was 8.2 (95% CI 1.9–35.0) compared with 1.3 (0.8–2.3) in exposed subjects with CC/CT genotypes. Relative Excess Risk due to Interaction (RERI) analyses confirmed a significant additive interaction effect (RERI=6.8; 95% CI: 0.64– 33.7; p<0.05). In explorative analyses, the most severe degree of sexual and emotional abuse also yielded significant interaction effects (p<0.05). This study revealed interactions between physical abuse and rs1360780 of the FKBP5 gene, confirming its role in the individual susceptibility to depression. Given the large effect sizes, rs1360780 could be included into prediction models for depression in individuals exposed to childhood abuse.

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INTRODUCTION

A dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis has been suggested as an important pathogenetic factor in depressive disorders (Holsboer, 1999, Holsboer, 2000).

Normalization of the HPA function was found to be a neuroendocrinological correlate of the clinical improvement of depression (Zobel et al., 2001). In search for the genetic and functional mechanisms underlying the HPA dysregulation in depression, recent research focused on genes involved in HPA-axis regulation, such as the genes coding for the corticotrophin-releasing hormone receptor 1 (Bradley et al., 2008) and for FKBP5 (Binder et al., 2004, Binder et al., 2008, Binder, 2009).

The FKBP5 gene is located on chromosome 6p21 and consists of 10 exons. The FKBP5 gene codes for FK506 binding protein 51 (FKBP5), a co-chaperone of hsp90 which regulates the glucocorticoid receptor (GR) sensitivity (Binder, 2009). FKBP5 is mainly expressed in the brain, and in a broad array of human cells, including muscle, liver, and thymus tissue (Gawlik et al., 2006). Functionally, cortisol induces the FKBP5 expression by activation of glucocorticoid-response-elements (Vermeer et al., 2003). In turn, FKBP5 binding to the GR reduces the GR affinity for cortisol and diminishes the amount of activated GR translocation to the cell nucleus (Wochnik et al., 2005).

Interestingly, common single nucleotide polymorphisms (SNPs) within the FKBP5 gene have been found to increase the FKBP5 protein expression, e.g. the high-induction allele (T) of the

FKBP5 gene SNP rs1360780 (Binder et al., 2004). In line with the pathophysiological model

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infants during a stress test: the rs1360780 T allele was directly associated with an increased cortisol response. Moreover, insecure-resistant attachment behavior interacted with rs1360780 T-allele increasing the cortisol response.

Depressed patients homozygote for the high-induction allele (T) of rs1360780 showed a significantly faster response to antidepressant treatment and suffered from more previous episodes than the carriers of the CT or CC genotypes (Binder et al., 2004). In the STAR*D study only the CT genotype but not the T allele was associated with depression in White non-Hispanics compared to controls (Lekman et al., 2008). In some clinical samples with smaller size no association was found (Gawlik et al., 2006, Papiol et al., 2007).

Following the approach of gene-environment-interactions (Caspi et al., 2003, Grabe et al., 2005, Grabe et al., 2010), Binder et al. investigated the interaction between SNPs of the

FKBP5 gene and childhood abuse in adult posttraumatic stress disorder (PTSD) (Binder et al.,

2008). They found four highly linked SNPs of the FKBP5 gene (including rs1360780) that interacted significantly with childhood abuse to predict PTSD but not depression scores in adulthood. The interaction between SNPs of the FKBP5 gene (including rs1360780) and childhood adversity in PTSD was confirmed in African Americans but not in European Americans (Xie et al.). A further study found interactions between SNPs of the FKBP5 gene (including rs1360780) and childhood trauma in adult suicide attempts, however in this study the common risk allele was protective (Roy et al.). As some studies have suggested that early life stress precedes the HPA axis hyperactivity observed in MDD (Heim and Nemeroff, 2001, Carpenter et al., 2004) an interaction between variations within the FKBP5 gene and

childhood abuse could be of relevance in adult depression too.

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was chosen as primary outcome because of the higher statistical power of dimensional outcomes. Significant results were then replicated in a second model using DSM-IV (American Psychiatric Association, 1994) lifetime major depressive disorder as outcome variable. This was done because of two reasons: 1. To replicate and confirm the BDI-II interaction findings with an different but correlated outcome that assesses the diagnosis of lifetime occurrence of depression derived from an interview. 2. To evaluate the putative relevance of the interaction findings for clinical depression which is of course different than the self-rated BDI-II score on depressive symptoms in the general population.

MATERIALS AND METHODS

SAMPLING AND PHENOTYPING METHODS Sample and Sample Recruitment

Data from the Study of Health in Pomerania (SHIP) were used (John et al., 2001, Grabe et al., 2005). The target population was comprised of adult German residents in northeastern Germany living in 3 cities and 29 communities, with a total population of 212,157. A two-stage stratified cluster sample of adults aged 20 to 79 years (baseline) was randomly drawn from local population registries. The net sample (without migrated or deceased persons) comprised 6,267 eligible subjects, of which 4,308 Caucasian subjects participated at baseline SHIP-0 between 1997 and 2001. Follow-up examination (SHIP-1) was conducted 5 years after baseline and included 3,300 subjects.

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refused participation in the LEGEND study. 132 subjects did not respond to repeated efforts of contact (at least three written invitations, 10 telephone calls and five home visits). 35 subjects agreed to participate but missed all appointments.

Among the 2400 subjects who participated in the LEGEND study, 134 subjects were excluded from the analyses because of unreliable information or inconsistencies in the interview according to the judgment of the interviewer and the supervisor. Additionally 47 subjects were excluded because of missing genetic data, 60 because of missing BDI-II values (n=45) or MDD diagnosis (n=19) and 2 because of missing data on the number of adult traumata. Thus, 2157 were eligible for the present gene-environment-interaction analyses (Table 1).

There were expected differences between the subjects of the LEGEND study (n=2400) and the other subjects from baseline (SHIP-0) regarding age (p<0.001) and sex (p=0.02), with the LEGEND subjects being younger and preferentially female (52.4%). Importantly, based on the DSM-IV, stem questions for depression (Wittchen et al., 1999) which were implemented in SHIP-0 (John et al., 2001), no differences emerged between the subjects from LEGEND (n=2400) and the other subjects at (SHIP-0) (p> 0.5).

Because of some missing values in the Childhood Trauma Questionnaire (CTQ) (Bernstein et al., 2003), physical abuse could be analyzed in 2144 subjects, emotional abuse in 2138 subjects, sexual abuse in 2140 subjects, physical neglect in 2119 subjects and emotional neglect in 2113 subjects. All participants gave written informed consent. SHIP and LEGEND were approved by the local Institutional Review Board and conformed to the principles of the Declaration of Helsinki.

Phenotype Measures

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as continuous outcome measure in all analyses. The distribution of the BDI-II scores dependent on the different qualities and levels of childhood trauma exposure is given in Table 2. The Childhood Trauma Questionnaire (CTQ) was used for self-report of childhood maltreatment including emotional, sexual and physical abuse as well as emotional and physical neglect (Bernstein et al., 2003). It has a total of 28 items rated on a five-point Likert scale with higher scores indicating higher exposure to traumatic experiences. In addition to a dimensional scoring procedure, the manual provides threshold scores to determine the severity of abuse and neglect (none = 0, low = 1, moderate = 2 and severe to extreme = 3). In independent studies, the CTQ was reported to have good reliability and validity; additionally, the five-factor model (i.e., the five subscales reflecting the different types of childhood trauma) has been empirically confirmed (Bernstein et al., 2003, Wingenfeld et al., 2010). Dichotomized variables (0 and 1 versus 2 and 3) were created for each dimension. To exploratively analyze the putative effects of higher childhood exposure on GxE a second set of analyses was calculated testing the five CTQ dimensions for none (reference category) versus mild or moderate or severe, respectively. To further explore the impact of increasing severity/frequency of abusive events a cumulative variable comprising only subjects with at least one severe traumatic category of emotional, physical and sexual abuse was created (Overall abuse severe category).

To evaluate lifetime diagnosis of major depressive disorder (MDD) and posttraumatic stress disorder (PTSD) the Munich-Composite International Diagnostic Interview (M-CIDI) was applied (Wittchen and Pfister, 1997). The M-CIDI is a standardized fully structured instrument for assessing psychiatric disorders over the life span according to DSM-IV criteria. The computerized version of the interview was used by clinically experienced interviewers (psychologists) in a face-to-face situation.

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84 % of the subjects agreed to audiorecording of their interviews. In weekly meetings, the interviewers were supervised and in difficult cases consensus diagnoses were made by clinical experts (HJG, CS, HJF). For quality and training reasons one randomly selected interview audiotape was double checked by two interviewers every 2 weeks.

Multiple studies regarding clinical validity and reliability of the M-CIDI had yielded excellent results for the inter-rater reliability and confirmed high clinical validity. Test-retest reliability analyses of the diagnosis of major depressive disorders revealed kappas between 0.62 and 0.77, for the diagnosis of PTSD kappa was 0.72 (Wittchen and Pfister, 1997). Likewise, the interviewer (n=17) had no impact on the lifetime-diagnosis of MDD (Logistic regression: OR=1, p=0.87, N=2247) or PTSD in our study (OR=1, p=0.97, N=2247).

In order to adjust for the putative impact of adult traumata on the interaction effects a variable comprising the number of adult traumata was generated based on the trauma list of the PTSD section of the diagnostic interview (DSM-IV). All traumatic items (n=10) except childhood sexual abuse were included into this adult trauma variable.

GENETIC METHODS

Genotyping

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genotyping efficiency of the GWA was 98.55 %. The genotype-rate for the FKBP5 gene SNP rs1360780 was 99.6%. Hardy-Weinberg-Equilibrium (HWE) of rs1360780 was p=0.080 in SHIP-0 and p=0.029 in SHIP-LEGEND. The difference in allele frequencies between the SHIP-0 (CC=48.9%, CT=42.9%, TT=8.2%) and the LEGEND sample (CC=48.0%, CT=44.0%, TT=8.0%) was very small indicating that a selection bias with respect to the genotype was not introduced by LEGEND.

For secondary analyses, 11 additional SNPs of the FKBP5 gene were identified that were

genotyped by the Affymetrix Human SNP Array 6.0. However, only 3 SNPs met the following criteria: Call rate > 95%, HWE >0.01 and MAF> 0.1 ( Table S1a/b). A LD plot is given as Figure S1 (Chromosomal Position: Figure S2).

SNPs were used as basis for generating the multidimensional scaling (MDS) plot that were available in both the HapMap III r3 dataset and in the imputed dataset of the SHIP cohort, fulfilling the following QC criteria: HWE test p-value > 10-6, SNP call rate > 95%, minor allele frequency > 1%. Finally, 494,375 SNPs went into the analysis. The MDS components were calculated using PLINK and the results were plotted in R (Figure S3).

STATISTICAL ANALYSES

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versus TC and CC) in the BDI Tobit regression model were tested in a second model using the interview based diagnosis of lifetime MDD according to DSM-IV (American Psychiatric Association, 1994) as categorical outcome. Conventional logistic regression analyses were calculated and results were expressed as odds ratios (OR). Genotype differences in susceptibility to childhood abuse were estimated by biologic interaction, which is measured by departure from an additive model (Rothman, 2002). For the quantification of the magnitude of an interaction effect the Relative Excess Risk due to Interaction (RERI) was calculated (Greenland et al., 2008, Grabe et al., 2009). The adjusted RERI is easily estimated using the basic formula for RERI (Rothman, 2002), as follows (OR=odds ratio):

RERI = OR TT genotype and abuse – OR TT genotype and no abuse – OR CC/CT genotypes and abuse +1

For these confirmatory RERI analyses using MDD we also applied a 95% confidence interval (CI). If the lower bound of 95%CI of RERI was > 0, then the two-sided p-value for the interaction is significant on an α-level of 0.05.

We first used a newly developed modified bootstrap approach to calculate an appropriate CI for RERI. This method was recommended by Nie and colleagues to handle low cell counts (Nie et al., 2010). This modified approach is based on regularized instead of conventional logistic regression (see Supplementary Materials) and is supposed to yield narrower CIs compared with Zou’s (Zou, 2008) formula (Nie et al., 2010). We additionally calculated the more commonly used formula by Zou. This formula yielded the identical results compared to modified bootstrap approach according to Nie. As Zou’s method is more widely used we report RERI results based on this method.

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effect of single observations (exposed subjects with MDD) on the statistic of interest we performed detailed regression diagnostics (Hosmer and Lemeshow, 2000).

All analyses were performed with STATA/MP software, version 10.1 (StataCorp LP, College Station, Texas, USA) and, if necessary, we used the free-ware R, version 2.11.1(Team, 2010) using the packages “glmnet”, “Design” (Harrell, 2001) and “boot” (see Supplementary Methods).

RESULTS

The sample characteristics are shown in Table 1. No direct effects of the TT genotype of rs1360780 on the BDI-II or MDD were found (p=0.25, adjusted for sex and age). No direct association was found between the five subdimensions of the CTQ and rs1360780 (Fisher’s exact test: p>0.1).

INTERACTION ANALYSIS FOR BDI-II

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The results of the explorative interaction analyses between the five CTQ dimensions testing none (reference category) versus mild or moderate or severe (separately) and the CC/CT versus the TT genotypes with regard to BDI-II scores are shown in Table S3a/b. Tobit regression analyses revealed a significant interaction between the TT genotype and emotional (p=0.048) and sexual abuse (p=0.004) but not for the neglect dimensions (p>0.3) in the none versus severe condition.

To further explore the impact of increasing severity/frequency of abusive events a cumulative variable comprising only subjects with at least one severe (versus none, mild, moderate) traumatic category of emotional, physical and sexual abuse was created (Table S4). A significant interaction between this overall abuse variable and the CC/CT versus TT genotype emerged (p=0.007).

In Table S1a the secondary interaction results for the additional SNPs rs7757037, rs4713899, and rs9368881 are given for each genotype separately. The SNPs (rs4713899, rs9368881) linked to rs1360780 showed comparable results. However, no other SNP was superior to rs1360780 (rs4713899 had n=1 in the TT genotype/exposed group). Rs7757037 (r2=0.09 to rs1360780) showed no evidence of interaction.

INTERACTION ANALYSIS FOR MDD

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The interaction analysis for MDD indicated statistically significant effects (p<0.05) for the unadjusted RERI of 8.4 (95% CI: 0.78–39.0) and fully adjusted RERI of 6.8 (95% CI 0.46– 33.7).

When excluding cases with PTSD the combination of the TT genotype with physical abuse showed an adjusted OR= 13.0 (95% CI: 2.4 - 70.6) for lifetime MDD. The corresponding adjusted RERI was 12.0 (95% CI: 1.3 - 69.5). Adjusting the analyses also for PTSD (no exclusion) a RERI of 5.8 (95% CI: 0.3 - 30.8) was obtained.

DISCUSSION

We identified an interaction between the TT genotype of rs1360780 and childhood physical abuse on the severity of present adult depressive symptoms. Carriers of the TT genotype who had been exposed to childhood physical abuse showed a mean BDI-II score of 17.4 compared to 10.0 for exposed subjects without the TT genotype. The effect of the primary analyses also survived Bonferroni correction for the testing of the five exposure dimensions. This result was confirmed for lifetime diagnosis of major depression according to DSM-IV. The lifetime prevalence of MDD was 23.9% in the exposed CC/CT carriers compared to 66.7 % in the exposed TT carriers. In Figure 1 and 2 and Table S1a it is clearly indicated that the interaction effect between rs1360780 and childhood physical abuse is represented by homozygote carriers of the T allele.

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subjects with none, mild, moderate categories also demonstrated significant interaction with rs1360780 (p=0.007, Table S4). These results indicate that all abuse dimensions with increasing severity contribute to the interaction effects. It is noteworthy that correlations between the five CTQ subdimensions were low to moderate (r = 0.11 to 0.56; see Table S5). The neglect dimension did not show a comparable interaction effect. Thus, the FKBP5 pathway seems to be more specific in mediating the psychobiological effects of abuse-related stress.

Our results clearly extend previous findings on the association of FKBP5 and mood disorders examined in clinical populations (Binder et al., 2004, Lekman et al., 2008). Especially when gene-environment interactions contribute to the pathophysiology of a distinct genetic marker non-replications of direct gene effects could occur because of low rates of childhood abuse exposure in the investigated samples (Gawlik et al., 2006, Papiol et al., 2007). Likewise, in our sample, no direct association between rs1360780 and depression was observed.

In secondary interaction analyses we additionally investigated three intronic SNPs from the

FKBP5 gene with different LDs (r2) to rs1360780: 0.09 for rs7757037, 0.41 for rs4713899, and 0.83 rs9368881 ( Figure S1). All four SNPs are widely distributed over the FKBP5 gene and cover different regions of the gene ( Figure S2). The less linked SNP rs7757037 showed no evidence of interaction whereas the other two SNPs also indicated interactions with abuse dimension ( Table S1a). However, the AA genotype of rs4713899 included only 1 exposed subject. Thus, none of these two SNPs was superior to rs1360780.

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childhood physical abuse and prevalence of 30-35 % of MDD ( Figure S4). However, the true value of a TT genotype screening in exposed subjects should be assessed longitudinally. It is noteworthy that our results are in line with previous studies associating the high-induction T-allele of rs1360780 with an altered cortisol response to experimental stress (Luijk et al., Ising et al., 2008), with faster response to antidepressant treatment (Binder et al., 2004) and with the susceptibility to PTSD after childhood maltreatment (Xie et al., Binder et al., 2008). According to the pathophysiological model the high-induction alleles of the FKBP5 gene are associated with a relative GR resistance (Binder et al., 2008, Binder, 2009) which could facilitate a long-lasting dysregulation of the HPA-axis after childhood abuse and thereby increasing the risk for MDD.

As rs1360780 was associated with the diagnoses of PTSD in former studies (6, 18), analyses were also performed excluding all subjects with PTSD (n=29) and adjusting for PTSD (see Table S2). All interaction effects remained largely unchanged indicating that our findings are valid for depression. To minimize a putative effect of cumulative adult traumatization on the interaction effects we also adjusted all analyses for the number of traumatic events from the PTSD interview section. This adjustment did not change the interaction results. However, in both cases, PTSD and the number of adult traumata could be a causal mediator and no confounder (Rothman, 2002). In conclusion, PTSD and adult traumata did not account for the observed interaction effect between physical abuse, rs1360780 and depression in our study.

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observation (see Tables S6 and S7). Moreover, the method applied is known for yielding relative large confidence intervals, thus we have chosen a rather conservative approach (Nie et al., 2010).

In order to avoid major selection effects (e.g., selected treatment samples) that may bias the results, we recruited the subjects from the general population (SHIP). From the baseline study (SHIP-0) that started in 1997 only 55.7 % could be included in the LEGEND study (2007-2010). Importantly, we have no evidence that lifetime depressive symptoms at baseline had influenced the later participation in LEGEND.

One strength of our study is that we analyzed two outcomes of depression: a dimensional depression score (BDI-II) and the lifetime diagnosis of major depression. There are obvious clinical differences between a self-report measure covering the last two weeks prior to the interview and an interview based lifetime diagnosis of MDD (DSM-IV). We analyzed the statistical association between both endpoints: The area under the ROC curve was 0.69 which indicates a weak relationship between BDI-II scores and MDD (Hosmer and Lemeshow, 2000). Thus, it is justified to consider MDD and BDI as two different measures.

In conclusion, our results support the role of the high-induction TT genotype of the rs1360780 polymorphism of the FKBP5 gene in the susceptibility to depressive disorders in the light of adverse, especially traumatic childhood events.

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DISCLOSURE

There are no conflicts of interest. External financial support in the past 5 years:

Hans Joergen Grabe: German Research Foundation; Federal Ministry of Education and Research Germany; speakers honoraria from Bristol-Myers Squibb, Eli Lilly, Novartis, Eisai, Wyeth, Pfizer, Boehringer Ingelheim, Servier and travel funds from Janssen-Cilag, Eli Lilly, Novartis, AstraZeneca and SALUS-Institute for Trend-Research and Therapy Evaluation in Mental Health.

Carsten Spitzer: Travel funds and speakers honoraria from Janssen-Cilag and Boehringer Ingelheim; research grant from the “Stiftung zur Aufarbeitung der SED-Diktatur.”

Christian Schwahn, Katja Appel, Jessie Mahler, Andrea Schulz, Kristin Fenske, Jan Stender: none.

Sven Barnow: German Research Foundation; Federal Ministry of Health Germany.

Ulrich John: German Research Foundation; German Cancer Aid; European Union; Federal Ministry of Education and Research Germany; Federal Ministry of Health; Social Ministry of the Federal State of Mecklenburg-West Pomerania of Germany.

Alexander Teumer: none.

Matthias Nauck: Research grants from the Federal Ministry of Education and Research Germany, BioRad Laboratories GmbH, Siemens AG, Zeitschrift für Laboratoriumsmedizin, Bruker Daltronics, Abbott, Jurilab Kuopio, Roche Diagnostics, Dade Behring, DPC Biermann and Becton Dickinson.

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Reiner Biffar: Research grants by Federal Ministry of Education and Research Germany, Ivoclar, Sirona, Dentsply, Kavo, Wieland Ceramics, GC, Heraeus, Dentaurum, Merz-Dental, the Krupp-Foundation, German Society of Dentistry (DGZMK), German Society of Prosthetic Dentistry and Dental Materials (DGZPW).

Harald J. Freyberger: German Research Foundation; Social Ministry of the Federal State of Mecklenburg-West Pomerania; Family Ministry of the Federal Republic of Germany; speakers honoraria from AstraZeneca, Lilly, Novartis and travel funds from Janssen-Cilag.

ACKNOWLEDGMENTS

SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the ‘Center of Knowledge Interchange’ program of the Siemens AG. This work was also funded by the German Research Foundation (DFG: GR 1912/5-1). HJG, KA and CS had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

We would like to thank Daniela Becker, Varinia Popek, Elena Stoll, Frauke Grieme, Matthias Becker, Daniela Schrader, Julia Schwanda, Daniel Grams and Andrea Rieck for their

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Titles and Legends to figures:

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Table 1: Descriptive statistics of the sample (Mean ± standard deviation or number and percentages are given).

Participants BDI-II a,b MDDc

Characteristic No. % P Value yes % no % P Value

Overall 2157 6.4 ± 7.2 370 17.2 1787 82.8 age, years 2157 55.8 ± 13.8 53.2 ± 12.7 56.4 ± 14.0 <0.001 Age, range 2157 29.4 – 89.8 29.4 – 89.8 30.0 – 85.3 Sex male 1021 47.3 5.7 ± 6.3 <0.001 117 31.6 904 50.6 <0.001 female 1136 52.7 7.0 ± 7.9 253 68.4 883 49.4 (School) education#

<10 years/ elementary school 629 30.3 7.4 ± 7.0 79 22.4 550 31.9 10 years/ junior high 1067 51.4 6.0 ± 7.4 <0.001 200 56.8 867 50.3 0.003 High school 136 6.6 6.2 ± 6.8 29 8.2 107 6.2 University degree 244 11.8 4.9 ± 5.7 44 12.5 200 11.6 Employment status#

Education 30 1.4 6.6 ± 8.3 9 2.6 21 1.2

Unemployed 246 11.8 7.5 ± 8.5 40 11.4 206 11.9 Housewife / Maternity leave 40 1.9 8.0 ± 7.6 <0.001 6 1.7 34 2.0 0.215

Retired 634 30.5 7.6 ± 6.8 94 26.7 540 31.3 Part-time employed 227 10.9 5.7 ± 6.6 44 12.5 183 10.6 Fully employed 899 43.3 5.2 ± 6.7 159 45.2 740 42.9 Social welfare# No 2063 99.4 6.3 ± 7.1 0.034 348 98.9 1715 99.5 0.254 Yes 13 0.6 13.3 ± 10.6 4 1.1 9 0.5

Household monthly income#

<899 € 211 10.4 8.5 ± 8.4 42 12.1 169 10.0 900 – 2299 € 1225 60.3 6.6 ± 7.1 <0.001 202 58.4 1023 60.6 0.324 2300 – 3299 € 416 20.5 5.4 ± 6.6 77 22.3 339 20.1

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Marital status#

Single, never married 265 12.3 5.9 ± 6.8 48 13.0 217 12.2 Married 1462 68.0 5.9 ± 6.8 <0.001 204 55.4 1258 70.6 <0.001 Divorced/married but living separately 242 11.3 8.0 ± 9.1 71 19.3 171 9.6

Widowed 182 8.5 8.7 ± 7.7 45 12.2 137 7.7

Number of traumata 2157 370 1787

mean ± SD 0.76 ± 0.96 0.99 ± 1.07 0.72 ± 0.92 1st quartile – median – 3rd quartile 0 – 1 – 1 0 – 1 – 1 0 – 0 – 1

Minimum – Maximum 0 – 7 0 - 7 0 – 5

No trauma 1048 48.6 5.4 ± 6.5 <0.001 137 37.0 911 51.0 <0.001 At least one trauma 1109 51.4 7.3 ± 7.7 233 63.0 876 49.0 Posttraumatic stress disorder#

No 2128 98.7 6.2 ± 7.0 <0.001 353 95.4 1775 99.4 <0.001 Yes 27 1.3 18.1 ± 14.1 17 4.6 10 0.6 Physical Abuse# No 2047 95.5 6.2 ± 7.0 <0.001 340 92.6 1707 96.1 0.008 Yes 97 4.5 11.0 ± 10.3 27 7.4 70 3.9 Emotional Abuse# No 2062 96.4 6.1 ± 6.9 <0.001 332 90.2 1730 97.7 <0.001 Yes 76 3.6 14.5 ± 11.3 36 9.8 40 2.3 Sexual Abuse# No 2062 96.4 6.2 ± 7.0 0.003 342 92.9 1720 97.1 <0.001 Yes 78 3.6 10.1 ± 10.9 26 7.1 52 2.9 Physical neglect# No 1776 83.8 5.9 ± 6.9 <0.001 291 79.9 1485 84.6 0.034 Yes 343 16.2 8.9 ± 8.1 73 20.1 270 15.4 Emotional neglect# No 1856 87.8 5.9 ± 6.7 <0.001 291 79.9 1565 89.5 <0.001 Yes 257 12.2 9.8 ± 9.8 73 20.1 184 10.5 rs1360780 CC/CT 1984 92.0 6.4 ± 7.2 0.774 335 90.5 1649 92.3 0.292 TT 173 8.0 6.2 ± 7.3 35 9.5 138 7.7

# N<2157 because of missing values.

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b For BDI-II comparing more than two groups, the observed means and standard deviations were compared using analysis of variance for equal variances

and Kruskall-Wallis test for unequal variances.

c For MDD, the observed numbers were tested for homogeneity using Fisher’s exact test

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Table 2: Estimated means (95% CI) of BDI-II values across groups of the putative interaction between the rs1360780 genotype and environment factor (none, mild versus moderate, severe) adjusting for sex, age and number of adult traumata.

Environment factor Environment factor absent; CT or CC Environment factor absent; TT Environment factor present; CT or CC Environment factor present; TT P value

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Table 3: Interaction between physical abuse and rs1360780 for MDD.

Analysis (logistic regression)

Subjects with MDD Subjects without MDD

Not adjusted Adjusted for age and sex

Adjusted for age, sex, and

number of adult traumata Exposed to physical abuse Genotype N N MDD risk

(%) Odds ratio 95% CI Odds ratio 95% CI Odds ratio 95% CI

No CC or CT 311 1572 16.5 1 1 1

No TT 29 135 17.7 1.1 0.7 – 1.7 1.1 0.7 – 1.7 1.0 0.7 – 1.6 Yes CC or CT 21 67 23.9 1.6 1.0 – 2.6 1.5 0.9 – 2.6 1.3 0.8 – 2.3 Yes TT 6 3 66.7 10.1 a 2.5 – 40.6 8.7 b 2.1 – 36.0 8.2 c 1.9 – 35.0

RERI 95% 8.4 0.78 – 39.0 7.05 0.37 – 34.3 6.80 0.46 – 33.7

a Data analysis for exact estimator is as follows: odds ratio = 10.1 (95% CI = 2.1 – 62.7);

Data analysis for jackknife estimator is as follows: odds ratio = 10.1 (95% CI = 2.0 – 51.9)

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